{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:45:14Z","timestamp":1785545114254,"version":"3.56.0"},"reference-count":30,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Mhealth Uhealth"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n The usage of consumer wearables (CWs; eg, fitness trackers and smartwatches) in the population has increased enormously within the last decade. This has resulted in a large amount of digital person-generated health data that could be used to answer vital research questions. However, little is currently known about the usage of CWs to collect health data from the population living in Germany.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to describe the ownership of consumer wearables and their usage for the collection of health data from the adult population living in Germany, as well as the motives for the collection of health data and the average wear times. In addition, this study also aimed to investigate sociodemographic and health- and behavior-related differences between the group of CW users and the group of nonusers.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We used data from the nationally representative survey \u201cGerman Health Update,\u201d which was conducted through telephone interviews in 2021 and 2022. The final sample comprised 4464 adults aged 18 years and older. We derived weighted prevalences for the usage of CWs, as well as adjusted odds ratios for the ownership and the usage of CWs and their association with sociodemographic and health- and behavior-related variables.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Of the adult population, 19.3% (843\/4459) owned a CW, of whom 77.8% (650\/842) used their CW to collect health data (which corresponds to 650\/4458, 15.0% of the adult population). Older people, people with a low income, and people with a lower level of physical activity (PA) were less likely to own a CW and were less likely to use it for the collection of health data. Of the CW users who collected health data, 47.2% (321\/650) wore their CW during nocturnal sleep. The most frequently named motives for the collection of health data with a CW were \u201cto observe my PA\u201d (544\/647, 85.0%), \u201cfor fun\u201d (508\/644, 79.0%), and \u201cfor support during exercising\u201d (423\/647, 66.3%). Women chose the motive \u201cto observe my PA\u201d and \u201cto increase my PA\u201d more often than men, whereas men chose the motive \u201cto observe health issues\u201d more often than women.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Adults living in Germany owning a CW are younger, have a higher income, and are more physically active than individuals who do not use a CW. This means that the population groups that would be in particular need of health care are not sufficiently represented in these health datasets. Researchers should consider the selectivity of CW users when planning to use CW health data to answer research questions.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/59199","type":"journal-article","created":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T16:19:28Z","timestamp":1749658768000},"page":"e59199-e59199","source":"Crossref","is-referenced-by-count":7,"title":["Consumer Wearable Usage to Collect Health Data Among Adults Living in Germany: Nationwide Observational Survey Study"],"prefix":"10.2196","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1213-516X","authenticated-orcid":false,"given":"Kristin","family":"Manz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5976-2515","authenticated-orcid":false,"given":"Susanne","family":"Krug","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8582-055X","authenticated-orcid":false,"given":"Charlotte","family":"K\u00fchnelt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7000-2250","authenticated-orcid":false,"given":"Johannes","family":"Lemcke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9840-0431","authenticated-orcid":false,"given":"Ilter","family":"\u00d6zt\u00fcrk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9811-1002","authenticated-orcid":false,"given":"Julika","family":"Loss","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,6,11]]},"reference":[{"issue":"45","key":"R1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-019-0121-1","article-title":"Best practices for analyzing large-scale health data from wearables and smartphone apps","volume":"2","author":"Hicks","journal-title":"NPJ Digit Med"},{"key":"R2","unstructured":"Absatz von Wearables weltweit in den Jahren 2014 bis 2022 (in Millionen St\u00fcck). 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